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Hypotheses and Version Spaces

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Conceptual Structures for Knowledge Creation and Communication (ICCS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2746))

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Abstract.

We consider the relation of a learning model described in terms of Formal Concept Analysis in [3] with a standard model of Machine Learning called version spaces. A version space consists of all possible functions compatible with training data. The overlap and distinctions of these two models are discussed. We give an algorithm how to generate a version space for which the classifiers are closed under conjunction.

As an application we discuss an example from predicitive toxicology. The classifiers here are chemical compounds and their substructures. The example also indicates how the methodology can be applied to Conceptual Graphs.

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References

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Author information

Authors and Affiliations

  1. Technische Universität Dresden, Germany

    Bernhard Ganter

  2. VINITI Moscow, Russia

    Sergei O. Kuznetsov

Authors
  1. Bernhard Ganter
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  2. Sergei O. Kuznetsov
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Editor information

Editors and Affiliations

  1. Institute of Algebra, University of Technology, Dresden, Germany

    Bernhard Ganter

  2. Semantics Technology and Applications Research Laboratory (STARLab), Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, B-1050, Brussels 5, Belgium

    Aldo de Moor

  3. Institut für Algebra, Technische Universität Dresden, 01062, Dresden, Germany

    Wilfried Lex

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Ganter, B., Kuznetsov, S.O. (2003). Hypotheses and Version Spaces. In: Ganter, B., de Moor, A., Lex, W. (eds) Conceptual Structures for Knowledge Creation and Communication. ICCS 2003. Lecture Notes in Computer Science(), vol 2746. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45091-7_6

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  • DOI: https://doi.org/10.1007/978-3-540-45091-7_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40576-4

  • Online ISBN: 978-3-540-45091-7

  • eBook Packages: Springer Book Archive

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